Improved PSO_AdaBoost Ensemble Algorithm for Imbalanced Data.

The Adaptive Boosting (AdaBoost) algorithm is a widely used ensemble learning framework, and it can get good classification results on general datasets. However, it is challenging to apply the AdaBoost algorithm directly to imbalanced data since it is designed mainly for processing misclassified samples rather than samples of minority classes. To better process imbalanced data, this paper introduces the indicator Area Under Curve (AUC) which can reflect the comprehensive performance of the model, and proposes an improved AdaBoost algorithm based on AUC (AdaBoost-A) which improves the error calculation performance of the AdaBoost algorithm by comprehensively considering the effects of misclassification probability and AUC. To prevent redundant or useless weak classifiers the traditional AdaBoost algorithm generated from consuming too much system resources, this paper proposes an ensemble algorithm, PSOPD-AdaBoost-A, which can re-initialize parameters to avoid falling into local optimum, and optimize the coefficients of AdaBoost weak classifiers. Experiment results show that the proposed algorithm is effective for processing imbalanced data, especially the data with relatively high imbalances.

Effects of Remifentanil Gradual Withdrawal Combined with Postoperative Infusion on Postoperative Hyperalgesia in Patients Undergoing Laparoscopic hysterectomy: A Factorial Design, Double-Blind, Randomized Controlled Trial.

Background: Remifentanil-induced hyperalgesia (RIH) increases the risk of persistent postoperative pain, making early postoperative analgesic therapy ineffective and affecting postoperative patient satisfaction. This study aimed to verify the effects of gradual withdrawal of remifentanil combined with postoperative pump infusion of remifentanil on postoperative hyperalgesia and pain in patients undergoing laparoscopic hysterectomy. Methods: This trial was a factorial design, double-blind, randomized controlled trial. Patients undergoing laparoscopic hysterectomy were randomly allocated to the control group, postoperative pump infusion of remifentanil group, gradual withdrawal of remifentanil group, or gradual withdrawal plus postoperative pump infusion of remifentanil group (n = 35 each). The primary outcome was postoperative mechanical pain thresholds in the medial forearm. The secondary outcomes included postoperative mechanical pain thresholds around the incision, pain numeric rating scale scores, analgesic utilization, awakening agitation or sedation scores, a 15-item quality of recovery survey, and postoperative complications. Results: Gradual withdrawal of remifentanil significantly increased postoperative pain thresholds versus abrupt discontinuation (P < 0.05), whereas postoperative infusion did not show significant differences compared to the absence of infusion (P > 0.05). The combined gradual withdrawal and postoperative infusion group exhibited the highest thresholds and had the lowest postoperative pain scores and analgesic requirements as well as the highest quality of recovery scores (P < 0.05). No significant differences were observed for agitation scores, sedation scores, or complication rates (P > 0.05). Conclusion: The novel combined gradual withdrawal and postoperative infusion of remifentanil uniquely attenuates postoperative hyperalgesia, pain severity, analgesic necessity, and improves recovery quality after laparoscopic hysterectomy.